Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.5 EMIN=102 EMAX=95 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.04

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    773.4569744  1.00000000  .500000000  102.000000  95.0000000
     1.3    617.1328571  1.05604530  1.31964135  105.265875  95.9499694
     2.2    578.7167491  .987291568  1.29017754  106.130054  94.9162265
     3.2    568.7901378  1.09738278  1.24339695  105.944784  94.7746267
     4.1    520.8024450  1.34428851  1.10119275  104.699012  93.8869652
     5.2    515.4277593  1.36348093  1.02726469  104.608828  93.9687856
     6.1    501.1910908  1.31908550  .710306881  104.348745  94.5334081
     7.1    501.1317924  1.30964805  .680208856  104.292075  94.6776080
     8.1    501.0638981  1.31120868  .698352248  104.323537  94.6261941
     9.1    501.0634385  1.30990155  .697066191  104.325291  94.6264923
    10.1    501.0632431  1.31031725  .697278176  104.323177  94.6269594

Run stopped after 10 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   707107.07768   176776.76942
  Residual               66      501.06324        7.59187
  Uncorrected Total      70   707608.14092

  (Corrected Total)      69     1639.41773

  R squared = 1 - Residual SS / Corrected SS =     .69437

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.310317246   .175596244   .959728032  1.660906460
  GSD         .697278176   .237712786   .222669285  1.171887067
  EMIN      104.32317713   .555167082 103.21475029 105.43160398
  EMAX      94.626959362   .824866471 92.980060314 96.273858409

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .1646    -.3296    -.5494
  GSD          .1646    1.0000     .3985    -.5416
  EMIN        -.3296     .3985    1.0000    -.1212
  EMAX        -.5494    -.5416    -.1212    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=1.14 EMIN=0.14 EMAX=0.03 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    .0395175805  1.00000000  1.14000000  .140000000  .030000000
     1.2    .0280068280  .995178942  1.14297001  .120081559  .033099820
     2.1    .0276655560  .994715692  1.14321073  .119576304  .036972713
     3.2    .0268028455  .919201744  1.15191604  .121162312  .037775768
     4.2    .0262704476  .800270180  1.14535125  .117958122  .038840433
     5.3    .0228724868  .336795684  .962437816  .123609928  .049690132
     6.3    .0222029992  .237109827  .921807571  .126621277  .047339980
     7.1    .0216468064  .149921741  .755211903  .128697165  .050939353
     8.1    .0215481942  .287102670  .695737134  .128445676  .049367164
     9.1    .0213779368  .237687898  .668781230  .127088594  .050451737
    10.1    .0213638516  .241099088  .646258379  .126339163  .050475132
    11.1    .0213634002  .244698175  .647226719  .126214090  .050360664
    12.1    .0213633825  .244487797  .646136319  .126221394  .050378109
    13.1    .0213633821  .244465292  .646315675  .126223724  .050377004
    14.1    .0213633821  .244470560  .646309594  .126223457  .050376961

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .54192         .13548
  Residual               66         .02136   3.236876E-04
  Uncorrected Total      70         .56328

  (Corrected Total)      69         .09399

  R squared = 1 - Residual SS / Corrected SS =     .77270

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .244470560   .135226582  -.025518023   .514459142
  GSD         .646309594   .183965707   .279010209  1.013608979
  EMIN        .126223457   .004911621   .116417090   .136029824
  EMAX        .050376961   .003598161   .043193000   .057560922

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.1134    -.5047    -.3449
  GSD         -.1134    1.0000     .4906    -.3851
  EMIN        -.5047     .4906    1.0000    -.1028
  EMAX        -.3449    -.3851    -.1028    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.65 EMIN=44 EMAX=1600 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    19620041.24  1.00000000  .650000000  44.0000000  1600.00000
     1.3    8664649.942  .951370855  1.44994944  641.321491  1674.57100
     2.3    8471310.479  1.15709300  1.35278134  621.787622  1740.14927
     3.3    8359519.359  1.13315869  1.33259471  612.440012  1772.37941
     4.3    8356263.636  1.14341824  1.50676051  610.248276  1824.12585
     5.5    8202262.618  3.32907962  3.81249341  .000000000  3398.86187
     6.3    6156118.251  .827800265  2.11629545  21.2838297  2344.19132
     7.2    6145754.681  .952911908  2.23523600  20.4443949  2403.44346
     8.1    5914565.915  .152255794  2.16164744  14.9010769  1890.48296
     9.2    5765527.631  -.42687091  1.85871713  10.8915110  1514.00156
    10.1    5697799.569  -.85260604  1.51571967  7.30056141  1260.98764
    11.2    5130818.901  -1.1287949  .878194060  .000000000  1126.97344
    12.4    4945166.588  -1.0820585  .801311489  .000000000  1154.88648
    13.2    4859905.342  -1.0473640  .727958719  14.6390269  1153.12667
    14.1    4666425.655  -.83188503  .622695482  69.8035551  1194.71602
    15.1    4644974.519  -.81020658  .480400119  98.1294008  1170.79196
    16.1    4640011.400  -.83340928  .532257157  80.0128201  1175.93644
    17.1    4639243.045  -.82938145  .525359946  80.0927073  1175.31015
    18.1    4638811.062  -.83008633  .522452074  76.6678241  1174.04272
    19.1    4638692.727  -.83142032  .525448644  73.4208489  1174.02187
    20.1    4638672.093  -.83319240  .527620193  71.7662892  1173.93520
    21.1    4638671.431  -.83321989  .528134347  71.6650844  1174.04962
    22.1    4638671.413  -.83327164  .528113648  71.6734719  1174.03659

Run stopped after 22 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  38242420.5956  9560605.14889
  Residual               43  4638671.41273   107876.07937
  Uncorrected Total      47  42881092.0083

  (Corrected Total)      46  13310902.1055

  R squared = 1 - Residual SS / Corrected SS =     .65151

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.833271637   .180122414 -1.196523104  -.470020171
  GSD         .528113648   .249983791   .023973287  1.032254009
  EMIN      71.673471913 156.42294432 -243.7834597 387.13040351
  EMAX      1174.0365940 78.355224711 1016.0182236 1332.0549645




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.3376     .6661     .2382
  GSD         -.3376    1.0000    -.6436     .4137
  EMIN         .6661    -.6436    1.0000    -.1665
  EMAX         .2382     .4137    -.1665    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1.46 GSD=.0385 EMIN=0.310 EMAX=0.435 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.04

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    4.108393648  1.46000000  .038500000  .310000000  .435000000
     1.3    3.570290566  1.44963647  .038075064  .393860979  .531914279
     2.4    3.511858707  1.49160278  .068386744  .374611965  .574892858
     3.1    3.511472041  1.51797243  .072005460  .382361165  .571663295
     4.1    3.510138390  1.50792076  .058545142  .374328220  .568862352
     5.1    3.509609021  1.49982895  .068912557  .374000357  .565294102
     6.1    3.509265606  1.50442186  .071290212  .376384719  .567459124
     7.1    3.509263610  1.50426993  .070921566  .376221999  .567664163
     8.1    3.509263577  1.50430478  .070889034  .376219570  .567652855
     9.1    3.509263575  1.50431923  .070877063  .376219485  .567652091

Run stopped after 9 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       14.39372        3.59843
  Residual               66        3.50926         .05317
  Uncorrected Total      70       17.90298

  (Corrected Total)      69        4.04924

  R squared = 1 - Residual SS / Corrected SS =     .13335

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.504319227  1.05669E+15 -2.10974E+15  2.10974E+15
  GSD         .070877063  2.75369E+15 -5.49792E+15  5.49792E+15
  EMIN        .376219485   .036011739   .304319727   .448119242
  EMAX        .567652091   .048080847   .471655583   .663648599

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    1.0000     .0000     .0000
  GSD         1.0000    1.0000     .0000     .0000
  EMIN         .0000     .0000    1.0000     .0000
  EMAX         .0000     .0000     .0000    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1.46 GSD=1.023 EMIN=1.58 EMAX=3.53 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    55.04233980  1.46000000  1.02300000  1.58000000  3.53000000
     1.2    54.88486455  1.55911257  1.19820934  1.52947081  3.44193810
     2.3    54.47434649  1.66038904  1.39659198  1.60038931  3.55957171
     3.3    53.43122651  2.26180973  2.60597208  1.07055256  4.86747714
     4.1    53.15884290  2.60015024  2.39546188  1.22906942  4.93409064
     5.1    52.72989529  2.83567130  2.25479694  1.43648994  4.96231825
     6.1    52.62094148  2.74641039  2.35273135  1.39499517  5.00203555
     7.1    52.51486943  2.80575017  2.25317345  1.44049617  5.05349505
     8.1    52.35579517  3.00894914  1.95762372  1.54461341  5.31514430
     9.1    52.29437085  3.03209522  2.10319230  1.49281486  5.43461762
    10.2    52.22940926  3.21636163  2.24038906  1.47773455  5.72152022
    11.1    52.15642899  3.47700000  2.36796674  1.46758584  6.13770929
    12.1    52.15228132  3.47700000  2.34722802  1.47349298  6.15610430
    13.1    52.15052758  3.47700000  2.31552139  1.48312116  6.17412348
    14.1    52.15052671  3.47700000  2.31589301  1.48313913  6.17403563

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4      406.85947      101.71487
  Residual               66       52.15053         .79016
  Uncorrected Total      70      459.01000

  (Corrected Total)      69       90.08871

  R squared = 1 - Residual SS / Corrected SS =     .42112

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         3.477000000  6.497547457 -9.495772064 16.449772064
  GSD        2.315893010  3.533607351 -4.739181698  9.370967719
  EMIN       1.483139127   .433417754   .617792661  2.348485593
  EMAX       6.174035625 11.245061850 -16.27745475 28.625526004

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .9780    -.7221     .9987
  GSD          .9780    1.0000    -.8288     .9754
  EMIN        -.7221    -.8288    1.0000    -.7285
  EMAX         .9987     .9754    -.7285    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:40
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLA
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	70
Syntax		MODEL PROGRAM ED=1 GSD=.19 EMIN=192 EMAX=230 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    8567532.949  1.00000000  .190000000  192.000000  230.000000
     1.4    5768052.836  .953023281  .187181397  240.272706  520.451250
     2.3    5557741.623  .978313415  .600631507  238.278425  530.661099
     3.2    5547035.261  .909928887  .896793742  232.807356  535.721638
     4.4    5204643.736  1.36557813  .866942561  198.478536  598.982813
     5.2    5179833.502  1.51286375  .975395077  216.048511  693.929008
     6.4    5102590.812  1.68801399  .907409586  225.064404  708.181091
     7.4    5065243.635  1.73504158  1.11110498  191.358520  716.486372
     8.3    5036559.968  1.82998592  1.06494798  196.876676  727.732924
     9.1    4983817.155  2.13845125  .856655291  222.588325  761.290138
    10.1    4982584.420  2.16604685  .905590053  221.376524  767.091147
    11.1    4981865.299  2.20080622  .942700482  221.488825  776.886397
    12.1    4980778.991  2.26075185  1.01850127  220.309685  799.055763
    13.1    4979852.074  2.32531819  1.07825593  219.291235  824.039816
    14.1    4979186.792  2.38014995  1.12335751  217.987153  847.892737
    15.1    4978991.055  2.41684847  1.14794143  217.285339  863.630802
    16.1    4978959.836  2.43921603  1.16589231  216.890776  872.971434
    17.1    4978956.052  2.45005817  1.17273320  216.813349  876.994178
    18.1    4978955.908  2.45206373  1.17478663  216.784332  877.821974
    19.1    4978955.900  2.45194101  1.17455673  216.790986  877.748103
    20.1    4978955.900  2.45193566  1.17455315  216.791419  877.743926

Run stopped after 20 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  11537747.0998  2884436.77495
  Residual               66  4978955.90018    75438.72576
  Uncorrected Total      70  16516703.0000

  (Corrected Total)      69  7248533.84286

  R squared = 1 - Residual SS / Corrected SS =     .31311

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         2.451935658  1.443751501  -.430607219  5.334478534
  GSD        1.174553145  1.189083805 -1.199529270  3.548635561
  EMIN      216.79141901 57.418632917 102.15141954 331.43141847
  EMAX      877.74392584 557.64388126 -235.6280059 1991.1158576




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .8864    -.2465     .9781
  GSD          .8864    1.0000    -.5091     .9169
  EMIN        -.2465    -.5091    1.0000    -.3536
  EMAX         .9781     .9169    -.3536    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1 GSD=.5 EMIN=105 EMAX=82 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    1949.977235  1.00000000  .500000000  105.000000  82.0000000
     1.4    1749.517952  1.02445601  .903524163  105.872348  83.1238579
     2.1    1678.108974  1.04356520  .897785875  106.595899  82.9085073
     3.2    1562.310152  1.22515195  .843257311  106.014147  81.3642927
     4.2    1530.061915  1.24873988  .785420981  105.836725  81.7136077
     5.1    1529.493101  1.30012223  .872834492  106.446810  80.7152546
     6.1    1463.001144  1.36215104  .583348172  105.404557  81.9377668
     7.1    1452.907175  1.32178894  .459890154  105.208664  83.0229885
     8.1    1451.266599  1.33278594  .431244188  105.273649  82.9254578
     9.1    1451.178065  1.32887007  .442931591  105.314554  82.8717462
    10.1    1451.165517  1.32835151  .438340043  105.293432  82.8945014
    11.1    1451.164244  1.32909715  .438979158  105.294602  82.8862209
    12.1    1451.164159  1.32892021  .438962716  105.295825  82.8877696

Run stopped after 12 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   604573.66336   151143.41584
  Residual               59     1451.16416       24.59600
  Uncorrected Total      63   606024.82752

  (Corrected Total)      62     7128.50903

  R squared = 1 - Residual SS / Corrected SS =     .79643

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.328920206   .097473585  1.133876014  1.523964398
  GSD         .438962716   .135018904   .168790512   .709134919
  EMIN      105.29582545   .898948480 103.49703369 107.09461720
  EMAX      82.887769565  1.464899860 79.956511716 85.819027414

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .1543    -.2774    -.4955
  GSD          .1543    1.0000     .2910    -.4480
  EMIN        -.2774     .2910    1.0000    -.0679
  EMAX        -.4955    -.4480    -.0679    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1.9 GSD=1.14 EMIN=0.14 EMAX=0.03 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    .0887645856  1.90000000  1.14000000  .140000000  .030000000
     1.1    .0543051172  1.89565941  1.14151703  .132507533  -.02313350
     2.2    .0487764149  1.89383329  1.14538951  .120504682  -.00822817
     3.1    .0425027443  1.75228229  1.31610859  .126205812  -.01191801
     4.1    .0404575062  1.66066081  1.41972438  .129259032  .001501907
     5.1    .0327095684  1.17864197  1.86560183  .141336910  -.00350512
     6.1    .0313628929  1.04917415  1.97314712  .156511683  -.01117408
     7.1    .0300327683  .831591550  2.08052765  .160728007  .000248960
     8.1    .0296029634  .630632492  2.17739017  .166222051  .003557649
     9.1    .0293526690  .428400158  2.26095000  .173134807  .005151646
    10.1    .0292529925  .283527738  2.30019186  .178475652  .007011997
    11.1    .0292076024  .196216238  2.30435589  .181866836  .008107820
    12.1    .0291881247  .151978311  2.28547016  .183201444  .009386793
    13.1    .0291690572  .130032378  2.24280459  .183172489  .010712779
    14.1    .0291222174  .110064090  2.10869816  .180748882  .014540096
    15.1    .0290216021  .143367189  1.76394848  .171156990  .022807171
    16.1    .0289422399  .244080401  1.47744054  .160645436  .028230539
    17.1    .0288768902  .349897289  1.46026085  .156211102  .026473385
    18.1    .0288606195  .261384425  1.64542431  .162155460  .024209429
    19.1    .0288441375  .281392616  1.54712548  .159283758  .026170174
    20.1    .0288437285  .289042827  1.53379712  .158867174  .026159706
    21.1    .0288436204  .287986559  1.53470704  .158863015  .026235578
    22.1    .0288436180  .287635132  1.53623115  .158916202  .026199033
    23.1    .0288436176  .287761535  1.53577351  .158900890  .026207840
    24.1    .0288436176  .287759714  1.53577632  .158900957  .026207884

Run stopped after 24 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .58807         .14702
  Residual               59         .02884   4.888749E-04
  Uncorrected Total      63         .61691

  (Corrected Total)      62         .13676

  R squared = 1 - Residual SS / Corrected SS =     .78909

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .287759714   .319883911  -.352326514   .927845942
  GSD        1.535776325   .573068417   .389069071  2.682483578
  EMIN        .158900957   .019137054   .120607800   .197194114
  EMAX        .026207884   .014355242  -.002516887   .054932656




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.2654    -.6241    -.1952
  GSD         -.2654    1.0000     .8648    -.8330
  EMIN        -.6241     .8648    1.0000    -.5876
  EMAX        -.1952    -.8330    -.5876    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1 GSD=1.65 EMIN=44 EMAX=1215 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.05

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    11445482.44  1.00000000  1.65000000  44.0000000  1215.00000
     1.3    7045640.814  .943532041  2.56007527  422.107735  1405.96535
     2.2    5693223.430  .146082708  1.86921960  307.752081  1865.44461
     3.1    3410116.971  .757926010  1.46406279  240.687464  2309.73617
     4.3    3348703.483  .722365374  1.38770148  228.047564  2338.73589
     5.2    3329948.865  .792928684  1.40114243  223.137989  2379.86457
     6.3    2883638.688  .722697361  1.72963110  .000000000  2572.16997
     7.1    2305839.891  -.56113138  .873942563  18.9122549  1308.23668
     8.3    2304604.659  -.57173227  .865909280  18.8083181  1298.44559
     9.3    2206697.832  -.69390277  .598103228  .000000000  1223.35503
    10.3    2166605.791  -.65750177  .508478597  53.8930630  1197.79974
    11.4    2123538.012  -.55767731  .544016549  75.5275455  1235.38278
    12.1    2113069.660  -.53890075  .468709936  97.3278633  1222.47675
    13.1    2110966.486  -.55194686  .465664608  81.0603464  1216.03847
    14.1    2110800.101  -.55052738  .464362759  85.1007372  1215.70009
    15.1    2110799.605  -.55035356  .464741567  84.9981268  1215.96504
    16.1    2110799.588  -.55037499  .464660452  85.0109209  1215.92523

Run stopped after 16 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  27767205.7921  6941801.44802
  Residual               36  2110799.58825    58633.32190
  Uncorrected Total      40  29878005.3803

  (Corrected Total)      39  11020155.8833

  R squared = 1 - Residual SS / Corrected SS =     .80846

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.550374990   .110103615  -.773675471  -.327074510
  GSD         .464660452   .155345159   .149605867   .779715038
  EMIN      85.010920927 81.983717353 -81.25976441 251.28160627
  EMAX      1215.9252302 77.195921590 1059.3646447 1372.4858157




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0088     .4575     .4339
  GSD         -.0088    1.0000    -.4711     .5025
  EMIN         .4575    -.4711    1.0000    -.1375
  EMAX         .4339     .5025    -.1375    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=14.6 GSD=13.8 EMIN=0.310 EMAX=1.1 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.12

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    4.935194050  4.00000000  13.8000000  .310000000  1.10000000
     1.1    4.911821234  4.00000000  13.7964818  .287095862  1.08624044
     2.1    4.493069330  4.00000000  13.7547519  .000000000  1.53356333
     3.1    4.487271238  4.00000000  13.6909842  .000000000  1.54729717
     4.1    4.473081186  4.00000000  13.4313587  .000000000  1.57256752
     5.1    4.424146333  4.00000000  12.4251597  .000000000  1.63816774
     6.4    3.918511541  4.00000000  6.71040826  .000000000  1.96721735
     7.2    3.917050506  3.99965342  6.58549499  .003277274  1.96943460
     8.2    3.539022383  3.69229111  1.97793192  .443289230  1.54031913
     9.2    3.536248807  3.68763421  1.94433423  .447029490  1.53613632
    10.1    3.442808682  3.51783167  2.00873022  .484613014  1.45943778
    11.2    2.887954598  2.75766786  .929144325  .515723283  1.41116122
    12.2    2.866036876  2.72371276  .900820961  .514566656  1.41208830
    13.1    2.835929809  2.70413842  1.03082393  .491818826  1.44297766
    14.1    2.789389830  2.60691555  .863279535  .483277109  1.45780166
    15.1    2.788817138  2.62747240  .880872374  .480178588  1.46282218
    16.1    2.788607951  2.61990085  .874360831  .480633933  1.46085727
    17.1    2.788383357  2.61242844  .869359029  .480992034  1.45745666
    18.1    2.787447502  2.58385175  .851306301  .481931332  1.44139994
    19.1    2.784694279  2.50913325  .808271881  .483728289  1.39401529
    20.2    2.760592555  2.13289624  .598355093  .491355221  1.14699968
    21.2    2.759820598  2.11021250  .585416024  .491610533  1.13236956
    22.1    2.753225849  2.06586319  .557875333  .486370187  1.10816830
    23.1    2.745859339  2.03745077  .502528313  .479077740  1.08727341
    24.1    2.745653447  2.04487497  .496803112  .478678936  1.09000463
    25.1    2.745644668  2.04057616  .493572711  .478863449  1.08704230
    26.1    2.745642647  2.04139298  .494909493  .478759197  1.08787220
    27.1    2.745642515  2.04133141  .494729039  .478766781  1.08783936
    28.1    2.745642276  2.04093205  .494253035  .478778762  1.08768580
    29.1    2.745642208  2.04064148  .494049768  .478779240  1.08759504
    30.1    2.745642201  2.04056634  .494039694  .478776933  1.08757757

Run stopped after 30 major iterations.
Optimal solution found.





Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       26.20861        6.55215
  Residual               59        2.74564         .04654
  Uncorrected Total      63       28.95426

  (Corrected Total)      62        5.51318

  R squared = 1 - Residual SS / Corrected SS =     .50199

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         2.040566344   .223524248  1.593295357  2.487837330
  GSD         .494039694   .287266015  -.080778274  1.068857662
  EMIN        .478776933   .035501663   .407738270   .549815597
  EMAX       1.087577573   .123886163   .839681932  1.335473213

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .4798     .1297     .7531
  GSD          .4798    1.0000    -.2968     .6834
  EMIN         .1297    -.2968    1.0000    -.1242
  EMAX         .7531     .6834    -.1242    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1.67 GSD=0.232 EMIN=1.89 EMAX=88 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.08

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    99216.24909  1.67000000  .232000000  1.89000000  88.0000000
     1.2    349.3717976  1.72466429  1.73755207  1.83282484  11.0015703
     2.3    349.0496428  1.72539379  1.74566723  1.83206183  11.1860429
     3.6    210.1741210  2.07099866  1.39725128  1.46429573  13.2530157
     4.3    161.7871084  2.28671747  1.17993884  1.56740431  14.4688532
     5.5    143.4436612  2.38644338  1.18720411  1.07953294  16.9291172
     6.2    140.6670665  2.41095074  1.16066474  1.13300258  17.0351637
     7.1    134.7692643  2.55846675  1.01583581  1.55901702  17.9458920
     8.1    133.8778104  2.51996026  1.05839913  1.47798934  17.8131850
     9.1    133.7841241  2.52866223  1.05237980  1.49040367  17.9372567
    10.1    133.7307230  2.53440560  1.04812262  1.49807307  18.0534775
    11.1    133.6959829  2.53471077  1.04579858  1.50051946  18.0850805
    12.1    133.5531085  2.52904413  1.03584406  1.50774951  18.0974325
    13.1    133.2424949  2.50693615  1.01337930  1.52028200  17.9460231
    14.1    132.2506302  2.42353088  .945023491  1.55236714  17.1785610
    15.2    123.7883900  1.98722237  .618019923  1.69305062  12.8486151
    16.2    123.6543480  1.97527515  .608500695  1.69597115  12.7269399
    17.1    122.3829423  1.95413791  .569992575  1.66536701  12.3741795
    18.1    121.7619128  1.97574254  .552241724  1.64758544  12.3458095
    19.1    121.7603588  1.97663980  .551665708  1.65277356  12.3398540
    20.1    121.7602145  1.97709726  .552476789  1.65179679  12.3440546
    21.1    121.7602043  1.97704675  .552606723  1.65162520  12.3436040

Run stopped after 21 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4     1909.75980      477.43995
  Residual               59      121.76020        2.06373
  Uncorrected Total      63     2031.52000

  (Corrected Total)      62      979.85714

  R squared = 1 - Residual SS / Corrected SS =     .87574

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.977046753   .095897543  1.785156212  2.168937294
  GSD         .552606723   .119207274   .314073519   .791139927
  EMIN       1.651625203   .244019299  1.163343713  2.139906693
  EMAX      12.343603960   .871870143 10.598995832 14.088212087




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .5209     .1188     .7834
  GSD          .5209    1.0000    -.3165     .7128
  EMIN         .1188    -.3165    1.0000    -.1384
  EMAX         .7834     .7128    -.1384    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLB
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	63
Syntax		MODEL PROGRAM ED=1 GSD=.19 EMIN=192 EMAX=667 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    1583819.000  1.00000000  .190000000  192.000000  667.000000
     1.4    1423642.174  1.09069753  1.69588132  186.195358  427.956697
     2.3    1213020.832  .559454470  1.40610442  156.366701  449.179681
     3.3    1074918.353  .765398843  1.32051561  146.780570  475.586544
     4.3    889514.8863  1.16947372  1.15680256  168.451241  527.505574
     5.5    777155.7678  1.20556387  1.04068531  151.395041  565.156478
     6.2    708114.1583  1.38701328  .973760450  156.254586  586.788812
     7.1    662664.6407  1.48002385  .882153637  161.090360  601.541474
     8.3    621039.2321  1.58249959  .722604239  171.475805  606.927439
     9.3    620755.1714  1.74359636  1.00057543  166.288541  691.153176
    10.2    615663.1771  1.74097949  .970121746  165.399160  692.694638
    11.1    596028.7327  1.84604396  .797388488  175.551359  698.008299
    12.1    594818.0281  1.78050505  .720324156  176.868266  679.386613
    13.1    594282.2105  1.74419711  .704275391  173.490616  666.724658
    14.1    594207.9395  1.75580467  .705600351  174.641423  668.015458
    15.1    594207.2434  1.75475238  .706069938  174.666594  667.815535
    16.1    594207.1707  1.75494622  .706041627  174.640288  667.871074
    17.1    594207.1704  1.75491414  .705981923  174.643482  667.856194

Run stopped after 17 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  7868778.82958  1967194.70739
  Residual               59   594207.17042    10071.30797
  Uncorrected Total      63  8462986.00000

  (Corrected Total)      62  2495174.88889

  R squared = 1 - Residual SS / Corrected SS =     .76186

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.754914141   .182361415  1.390009792  2.119818490
  GSD         .705981923   .222119323   .261522185  1.150441661
  EMIN      174.64348203 18.927195115 136.77025208 212.51671197
  EMAX      667.85619396 64.027877276 539.73670746 795.97568046




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .5662     .1027     .8173
  GSD          .5662    1.0000    -.3788     .7547
  EMIN         .1027    -.3788    1.0000    -.1815
  EMAX         .8173     .7547    -.1815    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1 GSD=.5 EMIN=102 EMAX=78 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bodyweig
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    748.2184451  1.00000000  .500000000  102.000000  78.0000000
     1.2    736.3388144  .998141316  .530668286  102.023782  77.9772181
     2.1    593.8884338  .936642578  .661011837  104.390732  75.7093022
     3.3    563.6981909  .871394100  .649321991  103.907514  74.9277124
     4.2    545.9106956  .804094378  .593742778  103.978011  76.3404911
     5.1    531.5056950  .829681563  .705588606  104.210626  75.8554541
     6.1    520.4695404  .744072549  .622328619  104.153173  77.8402295
     7.1    520.4323007  .743053057  .626806720  104.165826  77.8306382
     8.1    520.4317619  .742275795  .626646677  104.166199  77.8417362
     9.1    520.4316824  .742490264  .626879584  104.166478  77.8366322
    10.1    520.4316811  .742483097  .626843138  104.166409  77.8370622

Run stopped after 10 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BODYWEIG

  Source                 DF  Sum of Squares  Mean Square

  Regression              4   496889.27595   124222.31899
  Residual               50      520.43168       10.40863
  Uncorrected Total      54   497409.70764

  (Corrected Total)      53     5904.26105

  R squared = 1 - Residual SS / Corrected SS =     .91185

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED          .742483097   .089891534   .561930637   .923035557
  GSD         .626843138   .114442052   .396979512   .856706764
  EMIN      104.16640916   .716633587 102.72700824 105.60581008
  EMAX      77.837062215  1.717766661 74.386826335 81.287298095

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .4251    -.1970    -.7380
  GSD          .4251    1.0000     .4094    -.7061
  EMIN        -.1970     .4094    1.0000    -.1760
  EMAX        -.7380    -.7061    -.1760    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:41
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1 GSD=1.14 EMIN=0.14 EMAX=0.03 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR thymus
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.2    .0473119634  1.00000000  1.14000000  .140000000  .030000000
     1.2    .0250085104  .996722140  1.14054833  .133033860  -.01290189
     2.1    .0249747502  .995896794  1.14140522  .131967541  -.01159969
     3.1    .0237799244  .960102514  1.17442208  .133481427  -.01171701
     4.1    .0174061536  .628498691  1.47265413  .147981543  -.00731246
     5.1    .0162539760  .473190977  1.60594609  .155669386  -.00503130
     6.1    .0156577273  .308627795  1.74264412  .164417174  -.00433118
     7.1    .0154629991  .191348626  1.83652794  .171083339  -.00344669
     8.1    .0153941760  .104511767  1.90281912  .176327391  -.00375565
     9.1    .0153730369  .051571868  1.94017825  .179613423  -.00325060
    10.1    .0153636737  .024806928  1.95561181  .181324328  -.00341035
    11.1    .0153523326  .002807274  1.96257189  .182626788  -.00325735
    12.1    .0153219676  -.03439162  1.95932192  .184408809  -.00252456
    13.1    .0152526175  -.09120413  1.92294725  .186044128  -.00025281
    14.1    .0150639455  -.20135192  1.77886461  .186510301  .006940051
    15.1    .0147051329  -.35941320  1.40122830  .181397754  .023293915
    16.2    .0141155687  -.34042011  .911571505  .165949338  .038229420
    17.1    .0137089264  -.29722803  .724421025  .158346822  .043134123
    18.2    .0128561544  -.22158575  .641651284  .151121184  .044874040
    19.1    .0121996923  -.12322005  .843227746  .148084740  .036886397
    20.1    .0119226431  -.08240304  .692056822  .143442457  .038297121
    21.1    .0117888448  -.10707286  .665382823  .146289611  .038441322
    22.1    .0117688716  -.09035237  .676779746  .145905876  .037968425
    23.1    .0117655165  -.08075042  .678585518  .145793734  .037631837
    24.1    .0117654421  -.08046171  .680352968  .145864952  .037559721
    25.1    .0117654395  -.08037778  .679881786  .145854854  .037564842
    26.1    .0117654395  -.08040735  .679903854  .145855863  .037565329

Run stopped after 26 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable THYMUS

  Source                 DF  Sum of Squares  Mean Square

  Regression              4         .54211         .13553
  Residual               50         .01177   2.353088E-04
  Uncorrected Total      54         .55388

  (Corrected Total)      53         .11597

  R squared = 1 - Residual SS / Corrected SS =     .89855




                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.080407349   .093319359  -.267844798   .107030099
  GSD         .679903854   .128232378   .422341543   .937466164
  EMIN        .145855863   .004987349   .135838477   .155873249
  EMAX        .037565329   .004603083   .028319765   .046810893

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0478    -.4971    -.4394
  GSD         -.0478    1.0000     .5663    -.5330
  EMIN        -.4971     .5663    1.0000    -.1811
  EMAX        -.4394    -.5330    -.1811    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:42
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1 GSD=.65 EMIN=44 EMAX=1580 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR erod
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    34320042.67  1.00000000  .650000000  44.0000000  1580.00000
     1.2    12711819.05  .953220458  1.41952347  843.646431  1643.45837
     2.2    10533853.34  .209039611  1.06433821  791.561647  2394.97227
     3.3    9446690.003  .520742120  .977647813  762.898083  2426.57866
     4.3    8150379.464  .348551751  .842087316  656.021550  2544.55861
     5.4    7968303.629  .236886942  .966387939  624.830191  2585.63328
     6.1    6897497.790  .655069864  1.58974353  373.472313  2829.62692
     7.1    6111164.723  .378741100  1.61474134  212.435843  3103.35279
     8.3    5557568.708  .416021701  1.76112007  .000000000  3278.87764
     9.3    5547750.660  .388156148  1.71437454  7.07216772  3255.88383
    10.1    5510067.627  .242387428  1.56406142  .000000000  3140.10005
    11.1    5437404.652  .058776384  1.51621064  .000000000  2766.43386
    12.1    5390072.652  -.23424431  1.36682518  .000000000  2304.73991
    13.3    5221022.611  -.53826623  1.14661134  .000000000  1946.22953
    14.3    5046315.703  -.85246601  .902296651  .000000000  1617.23431
    15.1    4900947.221  -.95091513  .822063833  .000000000  1619.04557
    16.3    4842962.242  -.92667302  .786962353  .000000000  1632.53436
    17.2    4806609.983  -.90356425  .677076406  66.7371507  1588.67278
    18.1    4777533.470  -.87290530  .618791209  68.2109469  1589.83864
    19.1    4776565.097  -.86199624  .598290327  88.5680236  1583.88107
    20.1    4776471.523  -.86564515  .595563639  88.0115731  1580.22621
    21.1    4776465.220  -.86571996  .596613548  87.7424405  1579.96364
    22.1    4776465.003  -.86571049  .596446808  87.7882551  1580.00020

Run stopped after 22 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable EROD

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  39212724.0378  9803181.00944
  Residual               32  4776465.00300   149264.53134
  Uncorrected Total      36  43989189.0408

  (Corrected Total)      35  15775785.0613

  R squared = 1 - Residual SS / Corrected SS =     .69723

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         -.865710489   .199754294 -1.272596670  -.458824308
  GSD         .596446808   .311669434  -.038403055  1.231296671
  EMIN      87.788255051 238.21081435 -397.4312955 573.00780557
  EMAX      1580.0001986 183.35758756 1206.5130148 1953.4873825




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.1948     .5927     .3287
  GSD         -.1948    1.0000    -.7538     .6790
  EMIN         .5927    -.7538    1.0000    -.3754
  EMAX         .3287     .6790    -.3754    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:42
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1.46 GSD=.0385 EMIN=0.310 EMAX=1.28 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR ffa
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    6.784601025  1.46000000  .038500000  .310000000  1.28000000
     1.6    4.934714910  1.44167960  .038349095  .421643268  1.28527377
     2.4    4.363678096  1.47006420  .177019046  .599627191  1.27001222
     3.1    4.283048350  1.39390924  .322837758  .598972186  1.31809684
     4.1    4.158545152  1.38344201  .298029392  .549709406  1.32668141
     5.1    4.157543569  1.37878629  .303094966  .548209125  1.31631491
     6.1    4.154476689  1.36745698  .314211688  .540621032  1.32344552
     7.2    4.150469391  1.35681099  .311718683  .542531668  1.31851218
     8.1    4.141189903  1.33309197  .279866053  .538952864  1.29412169
     9.2    4.139808338  1.33387887  .271746282  .540928532  1.29355686
    10.1    4.138701376  1.32705800  .260888162  .543712892  1.28114872
    11.1    4.138100132  1.32220579  .255859148  .543322429  1.28307465
    12.1    4.138037281  1.32299136  .257207003  .544473816  1.28559643
    13.1    4.138033228  1.32268490  .256827604  .544242976  1.28507342
    14.1    4.138033227  1.32268387  .256837369  .544241745  1.28507306

Run stopped after 14 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable FFA

  Source                 DF  Sum of Squares  Mean Square

  Regression              4       29.87225        7.46806
  Residual               50        4.13803         .08276
  Uncorrected Total      54       34.01029

  (Corrected Total)      53        7.95473

  R squared = 1 - Residual SS / Corrected SS =     .47980

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.322683866   .136530407  1.048454473  1.596913260
  GSD         .256837369   .151382484  -.047223300   .560898037
  EMIN        .544241745   .048086845   .447656475   .640827015
  EMAX       1.285073063   .124727258  1.034550992  1.535595134

  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000    -.0474     .2546     .5277
  GSD         -.0474    1.0000    -.2574     .3449
  EMIN         .2546    -.2574    1.0000    -.0221
  EMAX         .5277     .3449    -.0221    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:42
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1.67 GSD=0.232 EMIN=1.89 EMAX=23 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR bilirubi
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 3.477; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.06

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.3    737.5349081  1.67000000  .232000000  1.89000000  23.0000000
     1.4    626.9367466  1.62885226  .789994736  3.13015039  23.2408918
     2.1    593.2176652  1.60846996  .782034806  3.09820687  23.7166389
     3.5    509.1066852  1.48189134  .688555293  2.72306980  22.5438958
     4.4    479.2928380  1.56194413  .661328585  3.11717608  28.2699245
     5.2    429.0027049  1.85678519  .948962754  1.93678312  35.1835207
     6.3    395.6922024  1.78907994  .864493474  1.76254971  33.8117878
     7.1    357.8343708  1.52366161  .556716983  1.86791728  27.6586427
     8.1    349.7734994  1.60979848  .565280839  1.68172990  28.7438029
     9.1    344.5158278  1.50576400  .491286965  1.86621224  25.8573413
    10.1    342.4655383  1.43688085  .435700756  1.95513632  23.8626387
    11.1    341.7393391  1.41516837  .406355336  1.94615023  23.2090202
    12.1    341.3066330  1.43240268  .401863393  1.85552076  23.5259119
    13.1    341.0717907  1.42396358  .400210789  1.88458232  23.2396554
    14.1    341.0708690  1.42439695  .400816587  1.88324572  23.2638151
    15.1    341.0708565  1.42430760  .400693312  1.88315471  23.2605678
    16.1    341.0708565  1.42431281  .400701631  1.88314889  23.2606882

Run stopped after 16 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable BILIRUBI

  Source                 DF  Sum of Squares  Mean Square

  Regression              4     4218.03914     1054.50979
  Residual               50      341.07086        6.82142
  Uncorrected Total      54     4559.11000

  (Corrected Total)      53     2769.13204

  R squared = 1 - Residual SS / Corrected SS =     .87683

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.424312805   .090103270  1.243335062  1.605290548
  GSD         .400701631   .108941981   .181885223   .619518039
  EMIN       1.883148895   .450001877   .979293525  2.787004265
  EMAX      23.260688172  2.497843638 18.243621572 28.277754773




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .6931     .0203     .8715
  GSD          .6931    1.0000    -.2809     .8108
  EMIN         .0203    -.2809    1.0000    -.1568
  EMAX         .8715     .8108    -.1568    1.0000

Constrained Nonlinear Regression

Notes
Output Created		04-FEB-2002 15:46:42
Comments		 
Input	Data	N:\YTO\TCDD\ABC kannat\SPSS\s242_abc_spss.sav
	Filter	WLC
	Weight	<none>
	Split File	<none>
	N of Rows in Working Data File	54
Syntax		MODEL PROGRAM ED=1 GSD=.19 EMIN=192 EMAX=1600 .
COMPUTE PRED_ = emin+(emax-emin)*(CDF.NORMAL(lg10(dose),ed,gsd)).
CNLR asat
  /OUTFILE='C:\TEMP\spss194\SPSSFNLR.TMP'
  /PRED PRED_
  /BOUNDS ED <= 4; ED >= -2; GSD <= 50; GSD >= .01; EMIN >= 0
  /CRITERIA STEPLIMIT 2 ISTEP 1E+20 .

Resources	Elapsed Time	0:00:00.07

All the derivatives will be calculated numerically.




  Iteration Residual SS          ED         GSD        EMIN        EMAX

     0.4    5490868.474  1.00000000  .190000000  192.000000  1600.00000
     1.3    5040132.178  1.15616623  2.78287996  182.005361  833.526664
     2.2    3899682.614  .230903256  1.96998135  128.648596  932.862627
     3.2    1867053.240  1.62439397  1.24534731  81.0853106  1494.28063
     4.4    1583900.947  1.46124786  1.09898902  71.4786947  1473.34362
     5.7    1434825.319  1.45836324  1.13974332  143.571938  1426.46759
     6.1    1051178.282  1.45546033  .898401235  172.891664  1471.16009
     7.3    948095.9704  1.37099727  .787719423  174.681846  1438.37258
     8.3    867012.2972  1.50153209  .764337031  189.491094  1565.21974
     9.2    848083.5616  1.45914332  .706981532  193.416290  1526.38959
    10.1    839604.3637  1.65072031  .803000739  197.397134  1786.53594
    11.1    832363.0461  1.57338875  .716643444  202.203059  1693.03698
    12.1    831899.7107  1.54853182  .705083548  202.347212  1659.64671
    13.1    831727.9164  1.50989031  .681098266  202.877953  1602.58998
    14.1    831682.5986  1.52325786  .688486825  202.711021  1622.11519
    15.1    831680.3905  1.52090168  .686934529  202.762945  1618.58813
    16.1    831680.3684  1.52065989  .686759793  202.767392  1618.21567
    17.1    831680.3684  1.52066601  .686761153  202.767701  1618.22305

Run stopped after 17 major iterations.
Optimal solution found.


Nonlinear Regression Summary Statistics     Dependent Variable ASAT

  Source                 DF  Sum of Squares  Mean Square

  Regression              4  17770090.6316  4442522.65790
  Residual               50   831680.36840    16633.60737
  Uncorrected Total      54  18601771.0000

  (Corrected Total)      53  7943102.83333

  R squared = 1 - Residual SS / Corrected SS =     .89530

                                           Asymptotic 95 %
                          Asymptotic     Confidence Interval
  Parameter   Estimate    Std. Error     Lower         Upper

  ED         1.520666008   .276958562   .964378365  2.076953651
  GSD         .686761153   .211594844   .261760402  1.111761905
  EMIN      202.76770110 25.414446585 151.72128283 253.81411937
  EMAX      1618.2230453 387.52063275 839.86494729 2396.5811434




  Asymptotic Correlation Matrix of the Parameter Estimates

                  ED       GSD      EMIN      EMAX

  ED          1.0000     .9213    -.2259     .9855
  GSD          .9213    1.0000    -.4067     .9361
  EMIN        -.2259    -.4067    1.0000    -.2957
  EMAX         .9855     .9361    -.2957    1.0000

